Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface

Turbulent mixing is a vital component of vertical particulate transport, but ocean global circulation models (OGCMs) generally have low-resolution representations of near-surface mixing. Furthermore, turbulence data are often not provided in OGCM model output. We present 1D parametrizations of wind-driven turbulent mixing in the ocean surface mixed layer that are designed to be easily included in 3D Lagrangian model experiments. Stochastic transport is computed by Markov-0 or Markov-1 models, and we discuss the advantages and disadvantages of two vertical profiles for the vertical diffusion coefficient Kz. All vertical diffusion profiles and stochastic transport models lead to stable concentration profiles for buoyant particles, which for particles with rise velocities of 0.03 and 0.003 m s−1 agree relatively well with concentration profiles from field measurements of microplastics when Langmuir-circulation-driven turbulence is accounted for. Markov-0 models provide good model performance for integration time steps of Δt≈30 s and can be readily applied when studying the behavior of buoyant particulates in the ocean. Markov-1 models do not consistently improve model performance relative to Markov-0 models and require an additional parameter that is poorly constrained

Emerging risks from marine heat waves

Recent marine heat waves have caused devastating impacts on marine ecosystems. Substantial progress in understanding past and future changes in marine heat waves and their risks for marine ecosystems is needed to predict how marine systems, and the goods and services they provide, will evolve in the future

Концепция разработки программного обеспечения для повышения эффективности ведения финансового учета на предприятии

Considered commonly used software for conducting financial activities in the enterprise. Analyzed the main disadvantages of the product. The concept of software development, enhancing the efficiency of financial accounting in the company on the platform "1C: Enterprise"

Light-dependent grazing can drive formation and deepening of deep chlorophyll maxima

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Moeller, H. V., Laufkötter, C., Sweeney, E. M., & Johnson, M. D. Light-dependent grazing can drive formation and deepening of deep chlorophyll maxima. Nature Communications, 10(1), (2019):1978, doi:10.1038/s41467-019-09591-2.Deep Chlorophyll Maxima (DCMs) are subsurface peaks in chlorophyll-a concentration that may coincide with peaks in phytoplankton abundance and primary productivity. Work on the mechanisms underlying DCM formation has historically focused on phytoplankton physiology (e.g., photoacclimation) and behavior (e.g., taxis). While these mechanisms can drive DCM formation, they do not account for top-down controls such as predation by grazers. Here, we propose a new mechanism for DCM formation: Light-dependent grazing by microzooplankton reduces phytoplankton biomass near the surface but allows accumulation at depth. Using mathematical models informed by grazing studies, we demonstrate that light-dependent grazing is sufficient to drive DCM formation. Further, when acting in concert with other mechanisms, light-dependent grazing deepens the DCM, improving the fit of a global model with observational data. Our findings thus reveal another mechanism by which microzooplankton may regulate primary production, and impact our understanding of biogeochemical cycling at and above the DCM.We thank the Sea Education Association and the students and crew of SEA Cruise S272 for collecting and sharing CTD cast data from the South Pacific. We also thank M. Lepori-Bui for assistance in assembling grazing data, A. Mignot for sharing global DCM estimates, J.G. John for providing the COBALT control simulations, E.B. Olson, M.G. Neubert, C.A. Stock, and J.P. Dunne for advice on model formulation, and B.E. Harden for valuable discussion. We thank members of the UCSB EEMB Department for helpful feedback on earlier versions of this manuscript. H.V.M. gratefully acknowledges an NSF Postdoctoral Fellowship (DBI-1401332) and a UBC Biodiversity Center Postdoctoral Fellowship

Incorporating terrain specific beaching within a lagrangian transport plastics model for Lake Erie

Mass estimates of plastic pollution in the Great Lakes based on surface samples differ by orders of magnitude from what is predicted by production and input rates. It has been theorized that a potential location of this missing plastic is on beaches and in nearshore water. We incorporate a terrain dependent beaching model to an existing hydrodynamic model for Lake Erie which includes three dimensional advection, turbulent mixing, density driven sinking, and deposition into the sediment. When examining parameter choices, in all simulations the majority of plastic in the lake is beached, potentially identifying a reservoir holding a large percentage of the lake’s plastic which in previous studies has not been taken into account. The absolute amount of beached plastic is dependent on the parameter choices. We also find beached plastic does not accumulate homogeneously through the lake, with eastern regions of the lake, especially those downstream of population centers, most likely to be impacted. This effort constitutes a step towards identifying sinks of missing plastic in large bodies of water

Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface

Turbulent mixing is a vital component of vertical particulate transport, but ocean global circulation models (OGCMs) generally have low-resolution representations of near-surface mixing. Furthermore, turbulence data are often not provided in OGCM model output. We present 1D parametrizations of wind-driven turbulent mixing in the ocean surface mixed layer that are designed to be easily included in 3D Lagrangian model experiments. Stochastic transport is computed by Markov-0 or Markov-1 models, and we discuss the advantages and disadvantages of two vertical profiles for the vertical diffusion coefficient Kz. All vertical diffusion profiles and stochastic transport models lead to stable concentration profiles for buoyant particles, which for particles with rise velocities of 0.03 and 0.003gmgs-1 agree relatively well with concentration profiles from field measurements of microplastics when Langmuir-circulation-driven turbulence is accounted for. Markov-0 models provide good model performance for integration time steps of "t≈30gs and can be readily applied when studying the behavior of buoyant particulates in the ocean. Markov-1 models do not consistently improve model performance relative to Markov-0 models and require an additional parameter that is poorly constrained

Global Modeled Sinking Characteristics of Biofouled Microplastic

Microplastic debris ending up at the sea surface has become a known major environmental issue. However, how microplastic particles move and when they sink in the ocean remains largely unknown. Here, we model microplastic subject to biofouling (algal growth on a substrate) to estimate sinking timescales and the time to reach the depth where particles stop sinking. We combine NEMO‐MEDUSA 2.0 output, that represents hydrodynamic and biological properties of seawater, with a particle‐tracking framework. Different sizes and densities of particles (for different types of plastic) are simulated, showing that the global distribution of sinking timescales is largely size‐dependent as opposed to density‐dependent. The smallest particles we simulate (0.1 μm) start sinking almost immediately around the globe and their trajectories take the longest time to reach their first sinking depth (relative to larger particles). In oligotrophic subtropical gyres with low algal concentrations, particles between 1 mm and 10 μm do not sink within the 90‐day simulation time. This suggests that in addition to the comparatively well‐known physical processes, biological processes might also contribute to the accumulation of floating plastic (of 1 mm–10 μm) in subtropical gyres. Particles of 1 μm in the gyres start sinking largely due to vertical advection, whereas in the equatorial Pacific they are more dependent on biofouling. The qualitative impacts of seasonality on sinking timescales are small, however, localised sooner sinking due to spring algal blooms is seen. This study maps processes that affect the sinking of virtual microplastic globally, which could ultimately impact the ocean plastic budget

Modeling submerged biofouled microplastics and their vertical trajectories

The fate of (micro)plastic particles in the open ocean is controlled by physical and biological processes. Here, we model the effects of biofouling on the subsurface vertical distribution of spherical, virtual plastic particles with radii of 0.01–1 mm. For the physics, four vertical velocity terms are included: advection, wind-driven mixing, tidally induced mixing, and the sinking velocity of the biofouled particle. For the biology, we simulate the attachment, growth and loss of algae on particles. We track 10,000 particles for one year in three different regions with distinct biological and physical properties: the low productivity region of the North Pacific Subtropical Gyre, the high productivity region of the Equatorial Pacific and the high mixing region of the Southern Ocean. The growth of biofilm mass in the euphotic zone and loss of mass below the euphotic zone result in the oscillatory behaviour of particles, where the larger (0.1–1.0 mm) particles have much shorter average oscillation lengths ( 5000 m). Our results show that the vertical movement of particles is mainly affected by physical (wind-induced mixing) processes within the mixed layer and biological (biofilm) dynamics below the mixed layer. Furthermore, positively buoyant particles with radii of 0.01–1.0 mm can sink far below the euphotic zone and mixed layer in regions with high near-surface mixing or high biological activity. This work can easily be coupled to other models to simulate open-ocean biofouling dynamics, in order to reach a better understanding of where ocean (micro)plastic ends up